Thejovathi Murari¹, L. Prathiba², Kranthi Kumar Singamaneni^3,*, D. Venu⁴, Vinay Kumar Nassa⁵, Rachna Kohar⁶, Satyajit Sidheshwar Uparkar⁷

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 1241-1256, 2022, DOI:10.32604/iasc.2022.020203

Abstract In recent times, big data analytics using Machine Learning (ML) possesses several merits for assimilation and validation of massive quantity of complicated healthcare data. ML models are found to be scalable and flexible over conventional statistical tools, which makes them suitable for risk stratification, diagnosis, classification and survival prediction. In spite of these benefits, the utilization of ML in healthcare sector faces challenges which necessitate massive training data, data preprocessing, model training and parameter optimization based on the clinical problem. To resolve these issues, this paper presents new Big Data Analytics with Optimal Elman Neural network (BDA-OENN) for clinical decision… More >

Puneet Garg^*, Ashutosh Dixit, Preeti Sethi

Computer Systems Science and Engineering, Vol.40, No.2, pp. 703-717, 2022, DOI:10.32604/csse.2022.019557

Abstract Opportunistic Networks (OppNets) is gaining popularity day-by-day due to their various applications in the real-life world. The two major reasons for its popularity are its suitability to be established without any requirement of additional infrastructure and the ability to tolerate long delays during data communication. Opportunistic Network is also considered as a descendant of Mobile Ad hoc Networks (Manets) and Wireless Sensor Networks (WSNs), therefore, it inherits most of the traits from both mentioned networking techniques. Apart from its popularity, Opportunistic Networks are also starting to face challenges nowadays to comply with the emerging issues of the large size of… More >

Mohammed Baz¹, Sabita Khatri², Abdullah Baz³, Hosam Alhakami⁴, Alka Agrawal², Raees Ahmad Khan^2,*

Computer Systems Science and Engineering, Vol.40, No.2, pp. 691-702, 2022, DOI:10.32604/csse.2022.019079

Abstract The rapid emergence of novel virus named SARS-CoV2 and unchecked dissemination of this virus around the world ever since its outbreak in 2020, provide critical research criteria to assess the vulnerabilities of our current health system. The paper addresses our preparedness for the management of such acute health emergencies and the need to enhance awareness, about public health and healthcare mechanisms. In view of this unprecedented health crisis, distributed ledger and AI technology can be seen as one of the promising alternatives for fighting against such epidemics at the early stages, and with the higher efficacy. At the implementation level,… More >

Prachi Agrawal¹, Khalid Alnowibet², Talari Ganesh¹, Adel F. Alrasheedi², Hijaz Ahmad³, Ali Wagdy Mohamed^4,5,*

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 817-829, 2022, DOI:10.32604/cmc.2022.019685

Abstract Recent years witness a great deal of interest in artificial intelligence (AI) tools in the area of optimization. AI has developed a large number of tools to solve the most difficult search-and-optimization problems in computer science and operations research. Indeed, metaheuristic-based algorithms are a sub-field of AI. This study presents the use of the metaheuristic algorithm, that is, water cycle algorithm (WCA), in the transportation problem. A stochastic transportation problem is considered in which the parameters supply and demand are considered as random variables that follow the Weibull distribution. Since the parameters are stochastic, the corresponding constraints are probabilistic. They… More >

Mohammad Riyaz Belgaum¹, Fuead Ali¹, Zainab Alansari², Shahrulniza Musa^1,*, Muhammad Mansoor Alam^1,3, M. S. Mazliham⁴

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 251-266, 2022, DOI:10.32604/cmc.2022.018211

Abstract Software-defined networking (SDN) plays a critical role in transforming networking from traditional to intelligent networking. The increasing demand for services from cloud users has increased the load on the network. An efficient system must handle various loads and increasing needs representing the relationships and dependence of businesses on automated measurement systems and guarantee the quality of service (QoS). The multiple paths from source to destination give a scope to select an optimal path by maintaining an equilibrium of load using some best algorithms. Moreover, the requests need to be transferred to reliable network elements. To address SDN’s current and future… More >

Yanghoon Kim¹, Jawon Kim², Hangbae Chang^3,*

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 679-694, 2022, DOI:10.32604/cmc.2022.015610

Abstract The medical convergence industry has gradually adopted ICT devices, which has led to legacy security problems related to ICT devices. However, it has been difficult to solve these problems due to data resource issues. Such problems can cause a lack of reliability in medical artificial intelligence services that utilize medical information. Therefore, to provide reliable services focused on security internalization, it is necessary to establish a medical convergence environment-oriented security management system. This study proposes the use of system identification and countermeasures to secure system reliability when using medical convergence environment information in medical artificial intelligence. We checked the life… More >

G. Reshma^1,*, Chiai Al-Atroshi², Vinay Kumar Nassa³, B.T. Geetha⁴, Gurram Sunitha⁵, Mohammad Gouse Galety⁶, S. Neelakandan⁷

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 621-634, 2022, DOI:10.32604/iasc.2022.019117

Abstract In recent years, intelligent automation in the healthcare sector becomes more familiar due to the integration of artificial intelligence (AI) techniques. Intelligent healthcare systems assist in making better decisions, which further enable the patient to provide improved medical services. At the same time, skin lesion is a deadly disease that affects people of all age groups. Skin lesion segmentation and classification play a vital part in the earlier and precise skin cancer diagnosis by intelligent systems. However, the automated diagnosis of skin lesions in dermoscopic images is challenging because of the problems such as artifacts (hair, gel bubble, ruler marker),… More >

Norah S. Farooqi¹, Mohamed O. Khozium^2,*

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 297-309, 2022, DOI:10.32604/iasc.2022.019060

Abstract Using Business Intelligence (BI) applications is a critical factor for modern enterprises’ success. BI is one of the key components that persistently required for the modern high-tech companies and industries were used to handle huge amounts of data in every minute of the operations. The existing literature suggested that the lack of dynamic decision making, accuracy, and the degree of flexibility are the key limitations for handling the operational data. Many industries and companies adopted the software-based solution; however, the intelligence is there due to the dependence of the operational engagement for each of the sectors. Therefore, artificial intelligence business… More >

El-Sayed M. El-kenawy¹, Hattan F. Abutarboush², Ali Wagdy Mohamed^3,4, Abdelhameed Ibrahim^5,*

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 2983-2995, 2021, DOI:10.32604/cmc.2021.019114

Abstract Machine learning (ML) has taken the world by a tornado with its prevalent applications in automating ordinary tasks and using turbulent insights throughout scientific research and design strolls. ML is a massive area within artificial intelligence (AI) that focuses on obtaining valuable information out of data, explaining why ML has often been related to stats and data science. An advanced meta-heuristic optimization algorithm is proposed in this work for the optimization problem of antenna architecture design. The algorithm is designed, depending on the hybrid between the Sine Cosine Algorithm (SCA) and the Grey Wolf Optimizer (GWO), to train neural network-based… More >

Mohamed Esmail Karar^1,2, Omar Reyad^1,3,*, Abdel-Haleem Abdel-Aty⁴, Saud Owyed⁵, Mohd F. Hassan⁶

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 4095-4111, 2021, DOI:10.32604/cmc.2021.019059

Abstract Smart precision agriculture utilizes modern information and wireless communication technologies to achieve challenging agricultural processes. Therefore, Internet of Things (IoT) technology can be applied to monitor and detect harmful insect pests such as red palm weevils (RPWs) in the farms of date palm trees. In this paper, we propose a new IoT-based framework for early sound detection of RPWs using fine-tuned transfer learning classifier, namely InceptionResNet-V2. The sound sensors, namely TreeVibes devices are carefully mounted on each palm trunk to setup wireless sensor networks in the farm. Palm trees are labeled based on the sensor node number to identify the… More >